In this pooled analysis of seven prospective cohort studies, we observed increased risks of ‘obesity-related cancers’, overall and of CRC and postmenopausal breast cancer associated with equivalent increments of general adiposity (BMI) and measures of body fat distribution (WC, HC, and WHR). Relative risk estimates were comparable across the different adiposity indices. For postmenopausal breast cancer, there was indication that increased risks were confined to women who never used HT. When mutually adjusting for all four anthropometric measures, which may be linked to different underlying biological mechanisms, BMI appeared to be an independent risk factor of ‘obesity-related cancers’, CRC, and postmenopausal breast cancer. In contrast, WC and WHR appeared to be independent risk factors of ‘other obesity-related cancers’, which we could not analyse separately due to low number of cases. To our knowledge, this is the first study of older adults to comprehensively compare anthropometric measures of general adiposity and body fat distribution, to examine and quantify the respective independent effects of these measures and to examine the shape of the dose–response relationship for cancers known to be obesity-related.
Our analysis does not corroborate the hypothesis that central adiposity is a superior predictor of CRC or postmenopausal breast cancer among older adults, as proposed by some previous studies (Pischon et al, 2006; Stolzenberg-Solomon et al, 2013; White et al, 2015). In contrast, and in line with our results, is an analysis of the NIH-AARP Diet and Health Study, where BMI, WC, and WHR were found to be equally discriminatory for colon cancer risk (Keimling et al, 2013). HC was not associated with risk of colon cancer in Keimling et al, while in our analysis HC virtually mirrored results for BMI, albeit effect sizes were slightly lower as compared to BMI. HC in disease models that do not account for BMI and/or WC is probably more indicative of general adiposity rather than an indicator of fat accumulation in the lower extremities reflected by a high correlation between HC and BMI (Pearson correlation ∼0.8 in our data). Mutual adjustment of obesity indicators may reduce heterogeneity across studies as observed in our data. This could indicate that BMI does not capture general adiposity equally well in all White Caucasians and that holding WC and HC constant, improves the interpretation of BMI as a measure of general adiposity.
Furthermore, in the Cancer Prevention Study-II Nutrition Cohort, positive associations between WC and BMI and postmenopausal breast cancer risk were reported, but only the association with BMI remained significant after mutual adjustment (Gaudet et al, 2014).
For postmenopausal breast cancer, early results from the Iowa Women Health Study suggested a statistically significant multiplicative interaction between BMI and WHR (Folsom et al, 2000). However, in subsequent reports that specifically tested interactions between BMI and indicators of central adiposity in relation to risk of CRC (Keimling et al, 2013) and breast cancer (Gaudet et al, 2015), no statistically significant associations were found. Our findings are in line with these more recent reports in that we did not find statistically significant multiplicative interactions between BMI and any of the three measures of body fat distribution.
For most of the cancer sites that we grouped into ‘other obesity-related cancers’ due to the small number of cases, previous studies reported somewhat stronger associations with regard to measures of central adiposity as compared to BMI, which is in line with our findings. For example, in the meta-analysis of Aune et al on pancreatic cancer, WHR yielded an overall RR of 1.19 (95% CI: 1.09–1.31), while that for BMI was 1.10 (95% CI: 1.07–1.14; Aune et al, 2012). Slightly stronger associations for WC and WHR, as compared to BMI, were also reported in the most recent WCRF/AICR pooled analyses for advanced prostate cancer (World Cancer Research Fund/American Institute for Cancer Research, 2014). We were not able to include prostate cancer in our analysis because of lack of data by stage.
In an analysis using data from the large EPIC prospective cohort, we reported previously that abdominal obesity, rather than general obesity, is a risk factor for the development of oesophageal adenocarcinoma and gastric cardia cancer (Steffen et al, 2015). In the prospective NIH-AARP cohort both overall adiposity (BMI) and abdominal adiposity (WC, WHR) were associated with a higher risk of oesophageal adenocarcinoma, but only BMI was associated with a higher risk of gastric cardia adenocarcinoma (O’Doherty et al, 2012). In an updated WCRF/AICR meta-analysis, BMI was more strongly associated with an increased risk of endometrial cancer compared to WC or WHR, although WC was also associated with an increased risk (Aune et al, 2015b). Similarly, an increased risk of ovarian cancer was reported with greater BMI and a marginally significant positive association with WC, but no association was found for HC or WHR (Aune et al, 2015a). We are not aware of studies investigating the role of body fat distribution and risk of cancers of the liver and gallbladder. The evidence with regard to BMI was judged convincing for both of these cancer sites by the most recent WCRF/AICR pooled analyses (World Cancer Research Fund/American Institute for Cancer Research., 2015a, b). For these last two cancer sites, further assessment of the impact of body fat distribution in future studies is warranted.
Although WC and WHR (and HC as noted above) have been interpreted as measures of body fat distribution, they may well also be markers of general adiposity (Anderson et al, 2015). In the current study, we saw that these measures have associations with cancer that are similar to those for BMI, but mostly when used in separate models. However, few studies have conducted mutual adjustments between BMI and measures of body fat distribution to try to clarify their independent roles. This is a limitation, which needs further assessment in future studies because it may provide insight into the biologic mechanisms underlying observed associations between adiposity and cancer risk (Keimling et al, 2013). Ideally, for mutual adjustment of BMI and measures of body fat distribution, residuals of measures of WC and/or HC should be used in order to retain the interpretability of BMI as an indicator of general adiposity and to avoid potential problems of multi-collinearity. Otherwise, BMI is not easily interpretable or becomes an indicator of muscularity rather than adiposity (Hu, 2008). It is also of note that WC, HC, and WHR have larger measurement errors compared with measurement of BMI, which may affect the reliability of respective risk estimates and calls for additional caution when comparing results between these indicators.
Links between greater adiposity and increased risk of many cancers are biologically plausible considering that obesity is related to a vast array of metabolic and physiological dysfunctions (Park et al, 2014). A number of these altered processes have specifically been implicated in cancer development; notably (1) abnormalities of insulin resistance and the IGF-I system; described as the insulin-IGF-I-insulin pathway, which may promote tumour development at many anatomic sites (Park et al, 2014; Renehan et al, 2015); (2) the impact of adiposity on the biosynthesis and bioavailability of endogenous sex steroids (e.g., oestradiol) which applies predominantly, but not exclusively, to postmenopausal breast, endometrial and ovarian cancers (Park et al, 2014; Renehan et al, 2015); our findings that obesity-associated risk of postmenopausal breast cancer was strongest in women, who never used HT support that hypothesis; (3) obesity induced low-grade chronic systemic inflammation; and (4) alterations in the levels of adipocyte-derived factors, known as adipokines (Lee et al, 2015). All of these proposed pathways have been extensively investigated in mechanistic studies and tested in epidemiological settings. For example, adiponectin, one of the most abundant adipokines, has been shown to be a key mediator in the development of several types of obesity-related cancers including endometrial, breast, advanced prostate, CRC, renal, and pancreatic (Dalamaga et al, 2012). Unlike most of the other adipose tissue derived adipokines, serum adiponectin is reduced in obesity and correlates inversely with BMI, WC, HC, and WHR, independently of age and menopausal status (Dalamaga et al, 2012). Migrating adipose progenitor cells, which can be found in high concentration in white adipose tissue and may acquire a tumour-promoting function, and the gut microbiome are two emerging mechanistic hypotheses linking obesity with cancer risk (Renehan et al, 2015).
Our study has some limitations that may affect the interpretation of the results. Despite the pooling of seven cohorts, we were not able to compare adiposity measures across all anatomical cancer sites with strong evidence of an association with obesity because of low numbers of cases. These cancer sites were therefore combined in ‘other obesity-related cancers’. For this reason, we could not investigate whether one or several of these cancers may have driven the observed associations with WC and WHR. Also related to the low number of cases, we were not able to sub-divide CRC in its anatomical sub-sites – knowing that effects sizes are more pronounced for cancers of the colon as compared to the rectum (World Cancer Research Fund/American Institute for Cancer Research, 2011) – or to sub-divide breast cancer by receptor status. However, associations with BMI appear to be unrelated to receptor status in postmenopausal women who have never used HT (Renehan et al, 2015).
Further limitations of our study are related to differences in study design between cohorts, including differences in length of follow-up and assessment of several covariates. In order to harmonise the data and variable definitions across cohorts, some covariates such as physical activity were only available in binary form (yes/no). Despite adjustment for the main confounding factors, namely smoking and physical activity, we cannot rule out confounding by other unmeasured factors, most importantly reproductive factors and diet. As these were not consistently available from all cohorts, we were not able to take these into account in our analyses. However, we do not expect risk estimates being noticeably confounded by diet as has been shown previously (Renehan et al, 2012). In the ESTHER study, BMI based on self-reported height and weight was the only adiposity indicator available. Although self-reported BMI may grossly underestimate prevalence of adiposity at the population level, ranking of individuals according to their BMI is less affected (Hu, 2008). Furthermore, study-specific risk estimates for ESTHER were consistent with the other cohorts and the summary estimates; excluding ESTHER from the meta-analysis had virtually no effect on the summary estimates (data not shown). Keeping ESTHER in our analysis also facilitates comparison of results with our companion paper, where we investigated the impact of overweight duration on obesity-related cancers (Arnold et al, 2016a). Finally, we did not a priori stratify our analysis by sex, mainly due to sample size considerations. However, in secondary analysis, largely similarly increased risks among men and women were observed for the investigated adiposity indicators (Supplementary Table S3).
Strengths of our study include the availability of harmonised individual-level data for the estimation of cohort-specific risk estimates. This allowed us to use the same exposure definitions, disease end points, and multivariate models in all included studies. Our investigation included only prospective cohort studies, which reduces the potential of biases that are often reason for concern in retrospective studies, for example, recall and selection bias. Individuals within each of our cohorts were largely White Caucasian, which adds further validity to our results because the effects of a given WC in a White population may be very different to the same WC in an Asian or African-American population. However, these potential ethic differences need to be evaluated in future studies. Further, we explored and compared, to our knowledge, for the first time in a pooled analysis of cohorts consisting of middle-aged and older adults, non-linear associations between BMI, WC, HC, and WHR for cancer sites known to be adiposity-related.